539 research outputs found

    Proceedings of the 4th field robot event 2006, Stuttgart/Hohenheim, Germany, 23-24th June 2006

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    Zeer uitgebreid verslag van het 4e Fieldrobotevent, dat gehouden werd op 23 en 24 juni 2006 in Stuttgart/Hohenhei

    A reliability-based particle filter for humanoid robot self-localization in Robocup Standard Platform League

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    This paper deals with the problem of humanoid robot localization and proposes a new method for position estimation that has been developed for the RoboCup Standard Platform League environment. Firstly, a complete vision system has been implemented in the Nao robot platform that enables the detection of relevant field markers. The detection of field markers provides some estimation of distances for the current robot position. To reduce errors in these distance measurements, extrinsic and intrinsic camera calibration procedures have been developed and described. To validate the localization algorithm, experiments covering many of the typical situations that arise during RoboCup games have been developed: ranging from degradation in position estimation to total loss of position (due to falls, ‘kidnapped robot’, or penalization). The self-localization method developed is based on the classical particle filter algorithm. The main contribution of this work is a new particle selection strategy. Our approach reduces the CPU computing time required for each iteration and so eases the limited resource availability problem that is common in robot platforms such as Nao. The experimental results show the quality of the new algorithm in terms of localization and CPU time consumption.This work has been supported by the Spanish Science and Innovation Ministry (MICINN) under the CICYT project COBAMI: DPI2011-28507-C02-01/02. The responsibility for the content remains with the authors.Munera Sánchez, E.; Muñoz Alcobendas, M.; Blanes Noguera, F.; Benet Gilabert, G.; SimĂł Ten, JE. (2013). A reliability-based particle filter for humanoid robot self-localization in Robocup Standard Platform League. Sensors. 13(11):14954-14983. https://doi.org/10.3390/s131114954S1495414983131

    Artificial Vision in the Nao Humanoid Robot

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    Projecte Final de Màster UPC realitzat en col.laboració amb l'Universitat Rovira i Virgili. Departament d'Enginyeria Informàtica i MatemàtiquesRobocup is an international robotic soccer competition held yearly to promote innovative research and application in robotic intelligence. Nao humanoid robot is the new RoboCup Standard Platform robot. This platform is the new Nao robot designed and manufactured by the french company Aldebaran Robotics. The new robot is an advanced platform for developing new computer vision and robotics methods. This Master Thesis is oriented to the study of some fundamental issues for the artificial vision in the Nao humanoid robots. In particular, color representation models, real-time segmentation techniques, object detection and visual sonar approaches are the computer vision techniques applied to Nao robot in this Master Thesis. Also, Nao’s camera model, mathematical robot kinematic and stereo-vision techniques are studied and developed. This thesis also studies the integration between kinematic model and robot perception model to perform RoboCup soccer games and RoboCup technical challenges. This work is focused in the RoboCup environment but all computer vision and robotics algorithms can be easily extended to another robotics fields

    Robot Detection Using Gradient and Color Signatures

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    Tasks which are simple for a human can be some of the most challenging for a robot. Finding and classifying objects in an image is a complex computer vision problem that computer scientists are constantly working to solve. In the context of the RoboCup Standard Platform League (SPL) Competition, in which humanoid robots are programmed to autonomously play soccer, identifying other robots on the field is an example of this difficult computer vision problem. Without obstacle detection in RoboCup, the robotic soccer players are unable to smoothly move around the field and can be penalized for walking into another robot. This project aims to use gradient and color signatures to identify robots in an image as a novel approach to visual robot detection. The method, Fastgrad , is presented and analyzed in the context of the Bowdoin College Northern Bites codebase and then compared to other common methods of robot detection in RoboCup SPL

    Distance Estimation based on Color-Block: A Simple Big-O Analysis

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    This paper explains how the process of reading the data object detection results with a certain color. In this case the object is an orange tennis ball. We use a Pixy CMUcam5 connecting to the Arduino Nano with microcontroler ATmega328-based. Then through the USB port, data from Arduino nano re-read and displayed. It’s to ensure weather an orange object is detected or not. By this process it will be exactly known how many blocks object detected, including the X and Y coordinates of the object. Finally, it will be explained the complexity of the algorithms used in the process of reading the results of the detection orange object

    Vision Based Tracking and Interception of Moving Target by Mobile Robot Using Fuzzy Control

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    This paper presents a simple Fuzzy Logic Controllers (FLC) based control strategy to solve the tracking and interception problem of a moving target by a mobile robot equipped with a pan-tilt camera. Before sending commands to the mobile robot, video acquisition and image processing techniques are employed to estimate the target’s position in the image plane. The estimate coordinates are used by a fuzzy logic controller to control the pan-tilt camera angles. The objective is to ensure that the moving target is always at the middle of the camera image plane. A second FLC is used to control the robot orientation and to guarantee the tracking and interception of the target. The proposed pan-tilt camera and robot orientation controllers’ efficiency has been validated by simulation under Matlab using Virtual Reality Toolbox

    Designing a minimal reactive goalie for the RoboCup SPL

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    This paper presents the basic design and implementation of a goalkeeper made according to the regulations of the two-legged Standard Platform League of the RoboCup Federation. The paper describes the perceptive schemas created using the architecture of the TeamChaos-URJC team as well as the action schemes designed to create a minimal reactive goalie. This player was tested in the 2009 German Open international competition. The results obtained there are analyzed and the future works derived from that analysis are presente

    Penalty Kick of a Humanoid Robot by a Neural-Network-Based Active Embedded Vision System

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    [[abstract]]This paper realizes the humanoid robotic system to execute the penalty kick (PK) of the soccer game. The proposed system includes the following three subsystems: a humanoid robot (HR) with 22 degree-of-freedom, a soccer with different colors, and a soccer gate. In the beginning, the HR scans the soccer field to find the gate and the soccer, which are randomly distributed in a specific region in the front of the gate. If a command for the PK of the soccer with specific color is assigned, the HR will be navigated by an active embedded vision system (AEVS). After the HR reaches a planned position and posture, the PK of the HR will be executed. Two key important techniques are developed and integrated into the corresponding task. One is the modeling using multilayer neural network (MNN) for different view angles, the other is the visual navigation strategy for the PK of the HR. In addition, the error sensitivities in the pan and tilt directions of these four visible regions are analyzed and compared. The proposed strategy of the visual navigation includes the following two parts: (i) the switched visible regions are designed to navigate the HR to the planned position, and (ii) the posture revision of the HR in the neighborhood of the soccer in order to execute the PK. Finally, a sequence of experiments for the PK of the HR confirm the effectiveness and efficiency of the propose methodology.[[conferencetype]]ĺś‹éš›[[conferencelocation]]Taipei, Taiwa
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